Present invention embodiments are related to systems and methods for analyzing unstructured text to identify a high level of intensity of negative sentiment, thoughts or beliefs. In particular, present invention embodiments are related to performing training on collections of text files, each of the collections being authored by a respective author and having a respective level of intensity of negative thoughts or negative beliefs, to produce at least one aggregated score and comparing the at least one aggregated score to at least one profile score of a text file for analysis to determine a collection that is closest to the text file for analysis.
Often, after an occurrence of a negative event, information authored by an initiator of the negative event is found on a computer network such as, for example, the Internet or other network, that, in hindsight, appear to be obvious clues that the negative event was about to happen. For example, after an occurrence of several recent negative events, postings on websites were found that were authored by initiators of the negative events and would lead one to believe that the recent negative events were about to occur. Since these clues are not truly discovered, no intervention is initiated to prevent negative events.